Positioning unmanned aerial vehicles as communication relays for surveillance tasks

When unmanned aerial vehicles (UAVs) are used to survey distant targets, it is important to transmit sensor information back to a base station. As this communication often requires high uninterrupted bandwidth, the surveying UAV often needs a free line-of-sight to the base station, which can be problematic in urban or mountainous areas. Communication ranges may also be limited, especially for smaller UAVs. Though both problems can be solved through the use of relay chains consisting of one or more intermediate relay UAVs, this leads to a new problem: Where should relays be placed for optimum performance? We present two new algorithms capable of generating such relay chains, one being a dual ascent algorithm and the other a modification of the Bellman-Ford algorithm. As the priorities between the number of hops in the relay chain and the cost of the chain may vary, we calculate chains of different lengths and costs and let the ground operator choose between them. Several different formulations for edge costs are presented. In our test cases, both algorithms are substantially faster than an optimized version of the original Bellman-Ford algorithm, which is used for comparison

Complement C4 Copy Number Variation is Linked to SSA/Ro and SSB/La Autoantibodies in Systemic Inflammatory Autoimmune Diseases

Objective Copy number variation of the C4 complement components, C4A and C4B, has been associated with systemic inflammatory autoimmune diseases. This study was undertaken to investigate whether C4 copy number variation is connected to the autoimmune repertoire in systemic lupus erythematosus (SLE), primary Sjögren's syndrome (SS), or myositis. Methods Using targeted DNA sequencing, we determined the copy number and genetic variants of C4 in 2,290 well-characterized Scandinavian patients with SLE, primary SS, or myositis and 1,251 healthy controls. Results A prominent relationship was observed between C4A copy number and the presence of SSA/SSB autoantibodies, which was shared between the 3 diseases. The strongest association was detected in patients with autoantibodies against both SSA and SSB and 0 C4A copies when compared to healthy controls (odds ratio [OR] 18.0 [95% confidence interval (95% CI) 10.2–33.3]), whereas a weaker association was seen in patients without SSA/SSB autoantibodies (OR 3.1 [95% CI 1.7–5.5]). The copy number of C4 correlated positively with C4 plasma levels. Further, a common loss-of-function variant in C4A leading to reduced plasma C4 was more prevalent in SLE patients with a low copy number of C4A. Functionally, we showed that absence of C4A reduced the individuals’ capacity to deposit C4b on immune complexes. Conclusion We show that a low C4A copy number is more strongly associated with the autoantibody repertoire than with the clinically defined disease entities. These findings may have implications for understanding the etiopathogenetic mechanisms of systemic inflammatory autoimmune diseases and for patient stratification when taking the genetic profile into account.publishedVersio

Planning for loosely coupled agents using partial order forward-chaining

We investigate a hybrid between temporal partial-order and forward-chaining planning where each action in a partially ordered plan is associated with a partially defined state. The focus is on centralized planning for multi-agent domains and on loose commitment to the precedence between actions belonging to distinct agents, leading to execution schedules that are flexible where it matters the most. Each agent, on the other hand, has a sequential thread of execution reminiscent of forward-chaining. This results in strong and informative agent-specific partial states that can be used for partial evaluation of preconditions as well as precondition control formulas used as guidance. Empirical evaluation shows the resulting planner to be competitive with TLplan and TALplanner, two other planners based on control formulas, while using a considerably more expressive and flexible plan structure.

Applying domain analysis techniques for domain-dependent control in TALplanner

A number of current planners make use of automatic domain analysis techniques to extract information such as state invariants or necessary goal orderings from a planning domain. There are also planners that allow the user to explicitly specify additional information intended to improve performance. One such planner is TALplanner, which allows the use of domain-dependent temporal control formulas for pruning a forward-chaining search tree. This leads to the question of how these two approaches can be combined. In this paper we show how to make use of automatically generated state invariants to improve the performance of testing control formulas. We also develop a new technique for analyzing control rules relative to control formulas and show how this often allows the planner to automatically strengthen the preconditions of the operators, thereby reducing time complexity and improving the performance of TALplanner by a factor of up to 400 for the largest problems from the AIPS-2000 competition

TALplanner and Other Extensions to Temporal Action Logic

Though the exact definition of the boundary between\ud intelligent and non-intelligent artifacts has been a subject\ud of much debate, one aspect of intelligence that many would\ud deem essential is deliberation: Rather than reacting\ud ``instinctively'' to its environment, an intelligent system\ud should also be capable of reasoning about it, reasoning\ud about the effects of actions performed by itself and others,\ud and creating and executing plans, that is, determining which\ud actions to perform in order to achieve certain goals. True\ud deliberation is a complex topic, requiring support from\ud several different sub-fields of artificial intelligence.\ud The work presented in this thesis spans two of these\ud partially overlapping fields, beginning with reasoning about\ud action and change and eventually moving over towards\ud planning.\ud \ud The qualification problem relates to the difficulties\ud inherent in providing, for each action available to an\ud agent, an exhaustive list of all qualifications to the\ud action, that is, all the conditions that may prevent this\ud action from being executed in the intended manner. The\ud first contribution of this thesis is a framework for\ud modeling qualifications in Temporal Action Logic (TAL).\ud \ud As research on reasoning about action and change proceeds,\ud increasingly complex and interconnected domains are modeled\ud in increasingly greater detail. Unless the resulting models\ud are structured consistently and coherently, they will be\ud prohibitively difficult to maintain. The second\ud contribution of this thesis is a framework for structuring\ud TALdomains using object-oriented concepts.\ud \ud Finally, the second half of the thesis is dedicated to the\ud task of planning. TLplan pioneered the idea of using\ud domain-specific control knowledge in a temporal logic to\ud constrain the search space of a forward-chaining planner.\ud We develop a new planner called TALplanner, based on the\ud same idea but with several new extensions, some of which are\ud enabled by fundamental differences in the way the planner\ud verifies that a plan satisfies control formulas. TALplanner\ud generates concurrent plans and can take resource constraints\ud into account. The planner also applies several new\ud automated domain analysis techniques to control formulas,\ud further increasing performance by orders of magnitude for\ud many problem domains.\u

Tackling the Qualification Problem using Fluent Dependency Constraints: Preliminary Report

Recently, a great deal of progress has been made using nonmonotonic temporal logics to formalize reasoning about action and change. In particular, much focus has been placed on the proper representation of non-deterministic actions and the indirect effects of actions. One popular approach to representing the indirect effects of actions has been via the use of causal rules which in a more general sense can be viewed as fluent dependency constraints. Although fluent dependency constraints have been used primarily under a loose causal interpretation, we show that when interpreted in a broader sense they provide a flexible means for dealing with a number of other representational problems such as the qualification problem and the ramification constraints as qualification constraints problem, in addition to the standard ramification problem. More importantly, the use of fluent dependency constraints for different purposes does not involve additions to the base nonmonotonic temporal logic, TAL, used here, but simply the addition of several macro operators to an action language used to represent action scenarios or narratives. The payoff is that TAL has already been shown to offer a robust approach to representing action scenarios which permit incomplete specifications of both state and the timing of actions, non-deterministic actions, actions with duration, concurrent actions, use of both boolean and non-boolean fluents, and solutions to the frame and ramification problems for a wide class of action scenarios. In addition, all circumscribed action scenarios in these classes and the more general class involving qualification considered in this paper can be shown to be reducible to the first-order case. Finally, a restricted entailment method for this new class of scenarios is fully implemented. In the paper, we present a challenge example which incorporates all these features, propose a distinction between weak and strong qualification with a representation of both, and provide a visualization of the preferred entailments using a research tool VITAL for querying and visualizing action scenarios